Approach to automated detection of dominant errors in cloud provisions

A system configured to provision a machine in a cloud environment, the system comprising memory for storing instructions, and a processor configured to execute the instructions to:

• determine an inverse error frequency (IEF) value for pre-intervention errors in a set of intervention provisioning data;
• determine a dominant error for a provision during a provisioning step in the set of intervention provisioning data, wherein the dominant error for the provision during the provisioning step in the set of intervention provisioning data is a pre-intervention error that has a maximum IEF value;
• determine a duration frequency (DuF) value for each provision at the provisioning step for provisions in a set of non-intervention provisioning data;
• determine the dominant error for each provision during the provisioning step in the set of non-intervention provisioning data, wherein the dominant error for the provision during the provisioning step in the set of non-intervention provisioning data is as an error that resulted in the DuF value, computed as a maximum of error durations for the provision;
• determine based on the dominant error whether waiting a certain time period may enable the provisioning of the machine in the cloud environment to self-resolve without requiring the intervention when the provisioning step becomes stuck during the provisioning of the machine in the cloud environment;
• and
• progress with the provisioning of the machine in the cloud environment after the provisioning has self-resolved when the dominant error indicates that waiting the certain time period may enable the provisioning to self-resolve without requiring the intervention.

A computer program product for provisioning a machine in a cloud environment, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor of a system to cause the system to:

• determine an inverse error frequency (IEF) value for pre-intervention errors in a set of intervention provisioning data;
• determine a dominant error for a provision during a provisioning step in the set of intervention provisioning data, wherein the dominant error for the provision during the provisioning step in the set of intervention provisioning data is a pre-intervention error that has a maximum IEF value;
• determine a duration frequency (DuF) value for each provision at the provisioning step for provisions in a set of non-intervention provisioning data;
• determine the dominant error for each provision during the provisioning step in the set of non-intervention provisioning data, wherein the dominant error for the provision during the provisioning step in the set of non-intervention provisioning data is as an error that resulted in the DuF value, computed as a maximum of error durations for the provision;
• determine based on the dominant error whether waiting a certain time period may enable the provisioning of the machine in the cloud environment to self-resolve without requiring the intervention when the provisioning step becomes stuck during the provisioning of the machine in the cloud environment;
• and
• progress with the provisioning of the machine in the cloud environment after the provisioning has self-resolved when the dominant error indicates that waiting the certain time period may enable the provisioning to self-resolve without requiring the intervention.